In his mature writings, Kuhn describes the process of specialisation as driven by a form of incommensurability, defined as a conceptual/linguistic barrier which promotes and guarantees the insularity of specialties. In this paper, we reject the idea that the incommensurability among scientific specialties is a linguistic barrier. We argue that the problem with Kuhn’s characterisation of the incommensurability among specialties is that he presupposes a rather abstract theory of semantic incommensurability, which he then tries to apply to his description of (...) the process of specialisation. By contrast, this paper follows a different strategy: after criticising Kuhn’s view, it takes a further look at how new scientific specialties emerge. As a result, a different way of understanding incommensurability among specialties will be proposed. (shrink)

Following Hans-Jörg Rheinberger’s epistemological concept we show how a generic element of synthetic biology, the “biological switch”, can be integrated into an experimental system. Here synthetic biology is assumed to be a technoscience. Hence, the biological switch becomes a technoscientific research object. Consequently, the experimental system has to be analyzed in a technoscientific experimental setting, showing differences in comparison with the former. To work out the specific properties of the technoscientific experimental system, biological switching behavior is compared with the scientific (...) research object laser light in its classical setting. For the analyses, both the laser light and bistability, enabling a biological switch, are considered as epistemic things connected by the same theoretical concept of phase transitions. The so-called Schlögl model is used to model both biological switching behavior and induced emission of radiation and becomes an epistemic thing in itself. It becomes clear that the answer, whether one is dealing with the emission of laser light or with bistable switching behavior, is linked to the perspective taken. The technoscientific orientation towards applications and the development of basic scientific theories require different perspectives on one and the same epistemic thing, here also represented by the model. The research objects of synthetic biology as a technoscience thus also enter into the corresponding experimental systems as techno-epistemic objects. Their analysis leads to a more complete understanding of what constitutes synthetic biology. (shrink)

This paper analyzes the notion of possibility in biology and demonstrates how synthetic biology can provide understanding on the modal dimension of biological systems. Among modal concepts, biological possibility has received surprisingly little explicit treatment in the philosophy of science. The aim of this paper is to argue for the importance of the notion of biological possibility by showing how it provides both a philosophically and biologically fruitful category as well as introducing a new practically grounded way for its assessment. (...) More precisely, we argue that synthetic biology can provide tools to scientifically anchor reasoning about biological possibilities. Two prominent strategies for this are identified and analyzed: the design of functionally new-to-nature systems and the redesign of naturally occurring systems and their parts. These approaches allow synthetic biologists to explore systems that are not normally evolutionarily accessible and draw modal inferences that extend in scope beyond their token realizations. Subsequently, these results in synthetic biology can also be relevant for discussions on evolutionary contingency, providing new methods and insight to the study of various sources of unactualized possibilities in biology. (shrink)

Morphological engineering is an emerging research area in synthetic biology. In 2008 “synthetic morphology” was proposed as a prospective approach to engineering self-constructing anatomies by Jamie A. Davies of the University of Edinburgh. Synthetic morphology can establish a new paradigm, according to Davies, insofar as “cells can be programmed to organize themselves into specific, designed arrangements, structures and tissues.” It is obvious that this new approach will extrapolate morphology into a new realm beyond the traditional logic of morphological research. However, (...) synthetic morphology is a highly idealized vision of morphology which derives its visionary ideas from morphological engineering and mathematical idealizations in order to understand the principles of molecular morphology. Thus, the question is, if this approach will help to understand morphogenesis better or if it will just enable biologists to engineer morphogenesis. The paper investigates the development of synthetic morphology and its relation to synthetic biology as well as its epistemic gains. (shrink)

Inspired by the success of synthesising organic substances by Friedrich Wöhler in 1828, the vision of creating life in the laboratory synthetically has become increasingly accessible for today’s synthetic biology and synthetic genomics, respectively. The engineering of biology – a contemporary version of the liaison of technology and organic form – creates cellular machines, biobricks, biomolecular ‘borgs’, and entire synthetic genomes of artificial organisms. Besides major ethical concerns, the shift in scientific epistemology is of interest. Unlike classical analytical science, synthetic (...) science understands by a process of generation, through which myriads of new things are created, dramatically changing the living environment. (shrink)

In silicio design plays a fundamental role in the endeavour to synthesise biological systems. In particular, computer-aided design software enables users to manage the complexity of biological entities that is connected to their construction and reconfiguration. The software’s graphical user interface bridges the gap between the machine-readable data on the algorithmic subface of the computer and its human-amenable surface represented by standardised diagrammatic elements. Notations like the Systems Biology Graphical Notation , together with interactive operations such as drag & drop, (...) allow the user to visually design and simulate synthetic systems as ‘bio-algorithmic signs’. Finally, the digital programming process should be extended to the wet lab to manufacture the designed synthetic biological systems. By exploring the different ‘faces’ of synthetic biology, I argue that in particular computer-aided design is pushing the idea to automatically produce de novo objects. Multifaceted software processes serve mutually aesthetic, epistemic and performative purposes by simultaneously black-boxing and bridging different data sources, experimental operations and community-wide standards. So far, synthetic biology is mainly a product of digital media technologies that structurally mimic the epistemological challenge to take both qualitative as well as quantitative aspects of biological systems into account in order to understand and produce new and functional entities. (shrink)

Building computational models of engineered exemplars, or prototypes, is a common practice in the bioengineering sciences. Computational models in this domain are often built in a patchwork fashion, drawing on data and bits of theory from many different domains, and in tandem with actual physical models, as the key objective is to engineer these prototypes of natural phenomena. Interestingly, such patchy model building, often combined with visualizations, whose format is open to a wide range of choice, leads to the discovery (...) of new concepts and control structures. Two key questions are raised by this practice: how could discoveries arise from building external representations for which there is wide latitude in choice of the components from which they are built, and thus can be considered significantly arbitrary, and how could such discoveries allow engineering a real-world prototype system. To examine these questions, we present two case studies of discoveries that emerged from the building of such computational models in the bioengineering sciences. We then develop a process model that accounts for the discovery and transfer problems raised by both these cases, focusing on the process of building the model. Specifically, to account for the discovery problem, we propose that the process of building such models gradually leads to a close coupling between the modeler’s internal processes and the external dynamic model. To account for the transfer problem, we propose that the process of building the model leads to the creation of an enactive model that is generic, which closely enacts, and thus reveals, the way the system-level behavior of the engineered prototype emerges in time through the interaction of its parts. This enactive replication process leads to the model and the prototype forming a new class, which allows concepts and control structures developed for the computational model to be transfered to the real-world prototype. We argue that this account requires rethinking correspondence in engineering sciences as a plastic and enactive relation. A closer focus on the process of building models is required to develop a general account of this emerging approach to discovery. (shrink)